• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권10호
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• pp.5171-5189
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• 2016

With the popularity of cloud computing, many data owners outsource their graph data to the cloud for cost savings. The cloud server is not fully trusted and always wants to learn the owners' contents. To protect the information hiding, the graph data have to be encrypted before outsourcing to the cloud. The adjacent vertex search is a very common operation, many other operations can be built based on the adjacent vertex search. A boolean adjacent vertex search is an important basic operation, a query user can get the boolean search results. Due to the graph data being encrypted on the cloud server, a boolean adjacent vertex search is a quite difficult task. In this paper, we propose a solution to perform the boolean adjacent vertex search over encrypted graph data in cloud computing (BASG), which maintains the query tokens and search results privacy. We use the Gram-Schmidt algorithm and achieve the boolean expression search in our paper. We formally analyze the security of our scheme, and the query user can handily get the boolean search results by this scheme. The experiment results with a real graph data set demonstrate the efficiency of our scheme.

• 정보보호학회논문지
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• 제22권3호
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• pp.505-514
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• 2012

싸이월드, 페이스북과 같은 소셜 네트워킹 서비스는 개인적인 데이터를 지인들과 공유하는데 매우 유용하다. 이들은 대부분 중앙 집중형 서버를 기반으로 하는데, 이 같은 시스템은 사용자들의 모든 통신 내역이 서버에게 노출된다는 단점을 가진다. 이러한 문제점을 개선하기 위해서 p2p 시스템에 착안한 분산된 소셜 네트워킹 서비스와 그 안에서 타인의 데이터에 접근하는 것을 제어하는 연구가 진행 중이다. 기존의 접근제어 기법에서는 신뢰하는 제 3기관이 필요하거나 프로토콜에 참여하는 모든 사용자들이 온라인 상태여야 하고, 사용자들이 분산된 방식으로 구축한 소셜 네트워크가 서버에게 노출되는 단점이 존재했다. M. Atallah 등은 처음으로 암호학적인 키 관리 기법을 활용해서 기존의 기법들이 지닌 문제점을 모두 해결했지만, 제안된 기법이 매우 비효율적이라는 한계가 있었다. 본 논문에서는 이 기법이 가진 비효율을 분석하고, 키 관리 기법이 아닌 대칭키 기반의 환형(circular) 암호를 최초로 적용하여 효율적인 접근제어 기법을 제안한다. 제안하는 기법은 온라인 상에 구축된 소셜 네트워크를 통해서 사용자 데이터에 대한 접근을 분산된 방식으로 제어하고, 서버가 그 네트워크를 추론할 수 없도록 기존의 기법보다 향상된 효율성과 안전성을 제공한다.

• Journal of the Optical Society of Korea
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• 제15권3호
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• pp.244-251
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• 2011

We propose a new 2-step phase-shifting digital holographic optical encryption technique and analyze tolerance error for this cipher system. 2-step phase-shifting digital holograms are acquired by moving the PZT mirror with phase step of 0 or ${\pi}$/2 in the reference beam path of the Mach-Zehnder type interferometer. Digital hologram with the encrypted information is Fourier transform hologram and is recorded on CCD camera with 256 gray-level quantized intensities. The decryption performance of binary bit data and image data is analyzed by considering error factors. One of the most important errors is quantization error in detecting the digital hologram intensity on CCD. The more the number of quantization error pixels and the variation of gray-level increase, the more the number of error bits increases for decryption. Computer experiments show the results to be carried out encryption and decryption with the proposed method and the graph to analyze the tolerance of the quantization error in the system.

• International Journal of Advanced Culture Technology
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• 제10권2호
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• pp.240-245
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• 2022

Because of the importance of the information, encryption algorithms are heavily used. Raw data is encrypted and secure, but problems arise when the key for decryption is exposed. In particular, large-scale Internet sites such as Facebook and Amazon suffer serious damage when user data is exposed. Recently, research into a new fourth-generation encryption technology that can protect user-related data without the use of a key required for encryption is attracting attention. Also, data clustering technology using encryption is attracting attention. In this paper, we try to reduce key exposure by using homomorphic encryption. In addition, we want to maintain privacy through similarity measurement. Additionally, holistic similarity measurements are time-consuming and expensive as the data size and scope increases. Therefore, Min-Hash has been studied to efficiently estimate the similarity between two signatures Methods of measuring similarity that have been studied in the past are time-consuming and expensive as the size and area of data increases. However, Min-Hash allowed us to efficiently infer the similarity between the two sets. Min-Hash is widely used for anti-plagiarism, graph and image analysis, and genetic analysis. Therefore, this paper reports privacy using homomorphic encryption and presents a model for efficient similarity measurement using Min-Hash.